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- Piya Pal
- IEEE Transactions on Signal Processing
- 2010

A new array geometry, which is capable of significantly increasing the degrees of freedom of linear arrays, is proposed. This structure is obtained by systematically nesting two or more uniform linear arrays and can provide <i>O</i>(<i>N</i><sup>2</sup>) degrees of freedom using only <i>N</i> physical sensors when the second-order statistics of the received… (More)

- Piya Pal, P. P. Vaidyanathan
- 2011 Digital Signal Processing and Signal…
- 2011

A new approach to super resolution line spectrum estimation in both temporal and spatial domain using a coprime pair of samplers is proposed. Two uniform samplers with sample spacings MT and NT are used where M and N are coprime and T has the dimension of space or time. By considering the difference set of this pair of sample spacings (which arise naturally… (More)

- P. P. Vaidyanathan, Piya Pal
- IEEE Transactions on Signal Processing
- 2011

This paper considers the sampling of temporal or spatial wide sense stationary (WSS) signals using a co-prime pair of sparse samplers. Several properties and applications of co-prime samplers are developed. First, for uniform spatial sampling with M and N sensors where M and N are co-prime with appropriate interelement spacings, the difference co-array has… (More)

- Piya Pal, P. P. Vaidyanathan
- IEEE Transactions on Signal Processing
- 2015

A new framework for the problem of sparse support recovery is proposed, which exploits statistical information about the unknown sparse signal in the form of its correlation. A key contribution of this paper is to show that if existing algorithms can recover sparse support of size s, then using such correlation information, the guaranteed size of… (More)

- P. P. Vaidyanathan, Piya Pal
- IEEE Transactions on Signal Processing
- 2011

Coprime sampling and coprime sensor arrays have been introduced recently for the one-dimensional (1-D) case, and applications in beamforming and direction finding discussed. A pair of coprime arrays can be used to sample a wide-sense stationary signal sparsely, and then reconstruct the autocorrelation at a significantly denser set of points. All… (More)

- P. Pal, P. P. Vaidyanathan
- IEEE Transactions on Signal Processing
- 2012

Recently, direction-of-arrival estimation (DOA) algorithms based on arbitrary even-order (2<i>q</i>) cumulants of the received data have been proposed, giving rise to new DOA estimation algorithms, namely the 2<i>q</i> MUSIC algorithm. In particular, it has been shown that the 2<i>q</i> MUSIC algorithm can identify <i>O</i>(<i>Nq</i>) statistically… (More)

- Piya Pal, P. P. Vaidyanathan
- ACSCC
- 2012

In this paper, the problem of identifying the com mon sparsity support of multiple measurement vectors (MMV) is considered. The model is given by y[n] = Axs[n], 1::; n ::; L where {y[n]}�=l denote the L measurement vectors, A E nMXN is the measurement matrix and xs[n] E nN are the unknown vectors with same sparsity support denoted by the set So with ISol =… (More)

- P. P. Vaidyanathan, Piya Pal
- 2014 IEEE International Conference on Acoustics…
- 2014

A finite duration sequence exhibiting periodicities does not in general admit a sparse representation in terms of the DFT basis unless the period is a divisor of the duration. This paper develops a dictionary called the Farey dictionary for the efficient representation of such sequences. It is shown herein that this representation is especially useful for… (More)

- Chun-Lin Liu, P. P. Vaidyanathan, Piya Pal
- ISCAS
- 2016

- Piya Pal, P. P. Vaidyanathan
- IEEE Transactions on Signal Processing
- 2012

A new class of two dimensional arrays with sensors on lattice(s) is proposed, whose difference co-array can give rise to a virtual two dimensional array with much larger number of elements on a “dense” lattice. This structure is obtained by systematically nesting two arrays, one with sensors on a sparse lattice and the other on a dense lattice… (More)